方位概念"前/后"在汉语中的隐喻运用

从时间隐喻的角度出发,运用Antuano的特征选择理论和Boers变化参数理论,重点研究了汉语人称称谓中"前后"方位词的隐喻运用机制,同时解释了汉语中其他同"前后"搭配的 合成词的隐喻现象,从而证明了隐喻的运用是根源于人们的实践经验,受制于人们自身同周围环境相互作用的结果,这对于丰富汉语隐喻理论具有重要意义。     

转型时期的社会分化及其对社会稳定的影响

论述了我国社会转型时期,社会分化对原有的整合方式所构成的挑战。指出由于社会结构的快速分化,使得在社会分化和整合之间出现了断裂,这种断裂必将对社会稳定产生不可忽视的影响。因此,在当前社会转型的新形势下,为适应社会的急速分化,维护社会的稳定,我们必须建立一种新的社会整合方式,即培育中介组织,增强政府权威;建立健全法制,理顺利益关系;加强文化整合,重构价值体系等。     

多忠诚顾客与单一忠诚顾客探索行为的差异比较与分析

以基于行为和态度2个维度界定的多忠诚顾客和单一忠诚顾客为立足点,比较了这2类顾客探索行为之间存在的差异。然后,根据探索行为的动机来源,应用最优刺激水平理论解释了差异存在的真正原因。研究结论表明,多忠诚顾客的探索行为显著高于单一忠诚顾客的探索行为;多忠诚顾客感知品牌(店铺)能力和差异显著小于单一忠诚顾客,且感知品牌(店铺)能力,以及感知品牌(店铺)差异与探索行为存在显著负相关关系,以及2类顾客探索行为存在差异是由于他们感知品牌(店铺)能力的差异所导致的。     

A spatial structural equation model with an application to area health needs

Indices of population ‘health need’ are often used to distribute health resources or assess equity in service provision. This article describes a spatial structural equation model incorporating multiple indicators of need and multiple population health risks that affect need (analogous to multiple indicators–multiple causes models). More specifically, the multiple indicator component of the model involves health outcomes such as hospital admissions or mortality, whereas the multiple risk component models the impact on the need for area social and demographic indicators, which proxy population-level risk factors for different diseases. The latent need construct is allowed (under a Bayesian approach) to be spatially correlated, though the prior assumed for need allows a mix of spatially structured and unstructured influences. A case study considers variations in need for coronary heart disease (CHD) care over 625 small areas in London, using recent mortality and hospitalization data (the ‘indicators’) and measures of general ill-health, income and unemployment, which proxy variations in population risk for CHD.     

INLA or MCMC? A tutorial and comparative evaluation for spatial prediction in log-Gaussian Cox processes

We investigate two options for performing Bayesian inference on spatial log-Gaussian Cox processes assuming a spatially continuous latent field: Markov chain Monte Carlo (MCMC) and the integrated nested Laplace approximation (INLA). We first describe the device of approximating a spatially continuous Gaussian field by a Gaussian Markov random field on a discrete lattice, and present a simulation study showing that, with careful choice of parameter values, small neighbourhood sizes can give excellent approximations. We then introduce the spatial log-Gaussian Cox process and describe MCMC and INLA methods for spatial prediction within this model class. We report the results of a simulation study in which we compare the Metropolis-adjusted Langevin Algorithm (MALA) and the technique of approximating the continuous latent field by a discrete one, followed by approximate Bayesian inference via INLA over a selection of 18 simulated scenarios. The results question the notion that the latter technique is both significantly faster and more robust than MCMC in this setting; 100,000 iterations of the MALA algorithm running in 20 min on a desktop PC delivered greater predictive accuracy than the default INLA strategy, which ran in 4 min and gave comparative performance to the full Laplace approximation which ran in 39 min.     

Geometrically Corrected Second Order Analysis of Events on a Linear Network,with Applications to Ecology and Criminology

Abstract. We study point patterns of events that occur on a network of lines, such as road accidents recorded on a road network. Okabe and Yamada developed a ‘network K function’, analogous to Ripley's K function, for analysis of such data. However, values of the network K‐function depend on the network geometry, making interpretation difficult. In this study we propose a correction of the network K‐function that intrinsically compensates for the network geometry. This geometrical correction restores many natural and desirable properties of K, including its direct relationship to the pair correlation function. For a completely random point pattern, on any network, the corrected network K‐function is the identity. The corrected estimator is intrinsically corrected for edge effects and has approximately constant variance. We obtain exact and asymptotic expressions for the bias and variance of under complete randomness. We extend these results to an ‘inhomogeneous’ network K‐function which compensates for a spatially varying intensity of points. We demonstrate applications to ecology (webs of the urban wall spider Oecobius navus) and criminology (street crime in Chicago).     

空间计量经济学理论体系的解析及其展望

随着空间经济理论研究出现重大突破,空间计量经济学也从边缘走向现代计量经济学的主流。重点对空间计量经济模型的设立包括空间横截面数据模型、空间面板数据模型以及空间离散数据模型进行讨论,对模型参数估计方法包括最大似然估计法、两阶段最小二乘法和矩估计法等进行分析,对模型检验方法包括Moran’s I方法和LM/RS方法等内容进行总结,最后展望了该理论研究未来的发展趋势。     

中国区域经济差异空间分异特征及其机理研究

运用全局空间自相关指数、局部空间自相关指数和空间回归模型,从空间依赖性和异质性的角度分析中国区域经济差异空间分异的过程。研究发现:中国经济发达地区和欠发达地区空间集聚格局日趋显著,且东部和中西部区域分别演变成为经济发达地区和欠发达地区的相对集聚区。造成这一分异现象的成因是各种内生因子和宏观经济环境因子的区域间差异及其循环累积作用、空间自相关性的空间近邻效应及极化——涓滴效应。     

西安市居住空间分异特征及形成机理研究

随着城市化进程的加快,居住空间分异对城市空间格局的影响日益显著,并对居民的集群效应不断提高.近年来,古城西安通过旧城改造和新区建设,城市居住圈层正经历着分化与重构,故采用结构方程模型研究西安市居住空间分异特征及形成机理,研究结果表明:城市建设水平和区位地租是西安市居住空间分异形成的主要影响因素.     

中国地方政府官员的空间流动:层级分流模式与经验证据

政府官员的空间流动是中国国家治理和政府人事管理的一个重要制度安排。本文以周雪光（2016）的“层级分流”模式为出发点,提出政府官员空间流动与块上流动二元结构的实证假设,并发展出有关的概念工具和测量来分析政府人事流动网络结构。在此基础上,本文对某省1990-2008年间地级市与（部分）区、县、县级市及其所属机构主要官员人事流动的经验资料进行了系统性、整体性分析,主要包括：（1）层级分流的基本趋向;（2）条块权力结构;（3）块上流动形成的地方性人事网络结构诸方面。